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研究生:王詠文
研究生(外文):Yung-Wen Wang
論文名稱:應用低功率藍芽於耐延遲無線隨意網路之點對點訊息傳輸演算法
論文名稱(外文):A Novel P2P Short Message Transmission Algorithm for Delay-Tolerant MANETs with Bluetooth Low Energy
指導教授:郭斯彥郭斯彥引用關係
口試委員:雷欽隆顏嗣鈞陳俊良陳英一
口試日期:2015-06-25
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:電子工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:英文
論文頁數:49
中文關鍵詞:無線隨意網路耐延遲網路間歇性連接網路路由演算法低功秏藍芽
外文關鍵詞:Mobile Ad Hoc NetworksDelay Tolerant NetworksIntermittently Connected NetworksRouting algorithmBluetooth Low Energy
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近幾年由於智慧型手機以及平板裝置的興起,也帶動無線通訊技術如IEEE802.11、近場通訊、以及低功率藍芽快速發展,智慧裝置透過這些技術進行相互通訊而形成的網路又稱為「行動無線隨意網路」(Mobile Ad hoc Network)。 然而,行動無線隨意網路不依靠基地台或網路擷取點進行通訊,斷斷續續的節點狀況與快速變化的網路拓樸結構會使以往點對點傳輸之路由演算法並不穩定。基於以上的狀況,這類通訊中必須要有耐延遲(Delay-Tolerant)的特性,我們又稱這種網路「耐延遲行動無線隨意網路」(DTMs)。
在這篇論文中,由於人群的移動特性造就出手機裝置之間的移動相似性,屬於同一社群的人相遇的次數普遍會高於屬於不同社群的人,基於此特性,我們可以根據一些事前資訊建立出手機之間的社群網路模型,計算出每位節點幫忙轉傳訊息到終點的成功率來增加耐延遲網路的整體傳送成功率;而當網路狀況屬於穩定時,我們再切換成傳統行動無線隨意網路的演算法進行可靠傳輸。最後,我們使用Android手機得來的低功率藍芽的參數進行設計並且拿台大校園做為模擬情境,與其他現存的演算法進行比較,證實了我們的AL-DS演算法可以在不同的網路狀況下仍有穩定的傳輸成功率,並且隨著節點增加,傳輸的延遲會逐漸下降。


In the last few years, the introduction of smart phones and tablets with short range wireless communication techniques like IEEE802.11, NFC and Bluetooth Low Energy(BLE) has made the rapid development of Mobile Ad hoc network (MANET). However, algorithms for end-to-end based routing may not always be robust due to the sparse node density, frequent disruption of network topology and lacking of fixed infrastructures. With these natures, the communication needs to be delay-tolerant. We refer such networks as Delay-Tolerant MANETs(DTMs).
In this paper, for Delay Tolerant Network, we found that there is usually a homogeneous relationship between mobile nodes. It’s because of the nature that people in the same groups tend to meet each other more times than people in different groups. As a result, we use pre-defined information to make some social patterns and each node can use them to calculate the successful forwarding probability. As for those networks with high and stable node density, we use algorithms designed for MANET to establish a reliable data transfer. Moreover, we design the data structure for Android application to meet the standard of BLE.
At the end of this paper, we use the characteristics of Android BLE and NTU campus to construct a simulation model. Besides, we compare our method with different existing routing algorithms. The simulation result proves that our AL-DS algorithm can have stable delivery ratio regardless of the sparsity of network and lower delay when the nodes in the network increase.


口試委員會審定書 #
誌謝 i
中文摘要 ii
ABSTRACT iii
CONTENTS iv
LIST OF FIGURES vi
LIST OF TABLES viii
LIST OF ALGORITHM ix
Chapter 1 Introduction 1
Chapter 2 Related Works 3
2.1 MANETs 3
2.2 DTN Routing algorithms 5
2.3 Bluetooth Low Energy 8
2.4 AODV (Ad hoc On-Demand Distance Vector Routing) 10
2.5 Social-Similarity-based Routing in DTN 12
2.6 Hybrid MANET-DTN Routing Algorithms 13
Chapter 3 Proposed Algorithm 14
3.1 AODV-Like Algorithm (AL Algorithm) 16
3.1.1 Data Structures in AL algorithm 16
3.1.2 Algorithm in AL 18
3.2 DTN-Social similarity based algorithm (DS Algorithm) 21
3.2.1 Data Structures in DS algorithm 21
3.2.2 Algorithm in DS 22
3.3 Analysis of AL-DS 31
Chapter 4 Simulation models and results 35
4.1 Simulation Models 35
4.2 Simulation Results 38
Chapter 5 Conclusion and Future Works 46
REFERENCE 47


[1]C. Perkins and E. Royer, “Ad-hoc on-demand distance vector routing,” in Proc. WMCSA''99. Second IEEE Workshop on Mobile Computing Systems and Applications, 1999.
[2]D. Johnson, D. Maltz, and J. Broch, “DSR: the dynamic source routing protocol for multihop wireless ad hoc networks,” Ad Hoc Networking. Reading, MA: Addison-Wesley, 2001, ch.5.
[3]Y. Cao and Z. Sun, “Routing in Delay/Disruption Tolerant Networks: A Taxonomy, Survey and Challenges,” IEEE Commun. Surv. Tutorials, vol. 15, no. 2, pp. 654-677, 2013.
[4]A. Vahdat and D. Becker, “Epidemic routing for partially-connected ad hoc networks,” technical report, Duke Univ., 2000.
[5]T. Spyropoulos, K. Psounis and C. Raghavendra, “Efficient Routing in Intermittently Connected Mobile Networks: The Multiple-Copy Case,” IEEE/ACM Trans. Networking, vol. 16, no. 1, pp. 77-90, 2008.
[6]M. Grossglauser and D. Tse, “Mobility increases the capacity of ad-hoc wireless networks,” Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213), 2001.
[7]T. Spyropoulos, K. Psounis and C. Raghavendra, “Efficient Routing in Intermittently Connected Mobile Networks: The Single-Copy Case,” IEEE/ACM Trans. Networking, vol. 16, no. 1, pp. 63-76, 2008.
[8]M. Musolesi and C. Mascolo, “CAR: Context-Aware Adaptive Routing for Delay-Tolerant Mobile Networks,” IEEE Trans. on Mobile Comput., vol. 8, no. 2, pp. 246-260, 2009.
[9]K. Zhu, W. Li and X. Fu, “SMART: A Social- and Mobile-Aware Routing Strategy for Disruption-Tolerant Networks,” IEEE Transactions on Vehicular Technology, vol. 63, no. 7, pp. 3423-3434, 2014.
[10]M. Xiao, J. Wu and L. Huang, “Community-Aware Opportunistic Routing in Mobile Social Networks,” IEEE Trans. Comput., vol. 63, no. 7, pp. 1682-1695, 2014.
[11]C. Perkins and P. Bhagwat, “Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers,” SIGCOMM Comput. Commun. Rev., vol. 24, no. 4, pp. 234-244, 1994.
[12]D. Rothfus, C. Dunning and X. Chen, “Social-similarity-based routing algorithm in Delay Tolerant Networks,” 2013 IEEE International Conference on Communications (ICC), 2013.
[13]J. Lakkakorpi, M. Pitkänen and J. Ott, “Adaptive routing in mobile opportunistic networks,” in Proc. of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems - MSWIM ''10, 2010.
[14]J. Papaj, L. Dobos and R. Palitefka, “Candidate node selection based on trust for cognitive communication of mobile terminals in hybrid MANET – DTN,” 2014 5th IEEE Conference on Cognitive Infocommunications (CogInfoCom), 2014.
[15]M. Ito, H. Nishiyama and N. Kato, “A novel routing method for improving message delivery delay in hybrid DTN-MANET networks,” 2013 IEEE Global Communications Conference (GLOBECOM), 2013.
[16]C. Bettstetter, G. Resta and P. Santi, “The node distribution of the random waypoint mobility model for wireless ad hoc networks,” IEEE Trans. on Mobile Comput., vol. 2, no. 3, pp. 257-269, 2003.


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